Instructions to use niclas/model_en_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niclas/model_en_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="niclas/model_en_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/model_en_2") model = AutoModelForCTC.from_pretrained("niclas/model_en_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
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{"t": 0, "y": 1, "q": 2, "f": 3, "o": 4, "c": 5, "a": 6, "w": 7, "s": 8, "n": 10, "p": 11, "j": 12, "r": 13, "e": 14, "m": 15, "d": 16, "k": 17, "x": 18, "i": 19, "z": 20, "l": 21, "
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{"t": 0, "y": 1, "q": 2, "f": 3, "o": 4, "c": 5, "a": 6, "w": 7, "s": 8, "n": 10, "p": 11, "j": 12, "r": 13, "e": 14, "m": 15, "d": 16, "k": 17, "x": 18, "i": 19, "z": 20, "l": 21, "v": 22, "g": 23, "h": 24, "b": 25, "u": 26, "'": 27, "|": 9, "[UNK]": 28, "[PAD]": 29}
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